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From monolith to Lakebase to LTAP: rethinking the database from storage up
Tech Optimizer
July 2, 2026

From monolith to Lakebase to LTAP: rethinking the database from storage up

Sixteen years ago, the author began their PhD at UC Berkeley and was advised to focus on analytics rather than OLTP databases, which were considered solved. This led to the creation of Apache Spark and Databricks. However, during the development of Databricks, it was found that OLTP databases were not solved problems; they were difficult to scale and fragile. This realization led to the development of Lakebase, a serverless Postgres database designed with modern technology. Lakebase architecture separates the write-ahead log (WAL) and data files into independent, scalable services. The WAL is externalized to a service called SafeKeeper, which uses Paxos-based replication for durability, while data files are managed by PageServer, which stores them in cloud object storage. This design addresses challenges such as data loss, scaling, and performance interference between transactional and analytical workloads. Lakebase maintains compatibility with Postgres, offers unlimited storage, serverless compute, durable writes, and simpler high availability. It also introduces LTAP (Lake Transactional/Analytical Processing), which allows both transactional and analytical processing to operate on a single data copy in real time, eliminating the need for separate data copies and reducing costs. LTAP utilizes a unified storage layer that allows data to be materialized in both row and columnar formats, optimizing it for both transactional and analytical workloads. The system ensures that analytics can access the most current data without affecting transactional performance by using a log sequence number (LSN) to retrieve the latest changes. Unlike traditional CDC approaches, LTAP requires no explicit table replication, as all data is stored in a single governed copy. This architecture circumvents common issues faced by hybrid transactional/analytical processing (HTAP) systems, such as incomplete feature sets, lack of ecosystem support, and performance contention. The Lakebase architecture has unlocked capabilities like unlimited storage, elastic compute, durable writes, and instant branching, with ongoing developments anticipated in the future.
silver Android smartphone
Tech Optimizer
July 2, 2026

From monolith to Lakebase to LTAP: rethinking the database from storage up

Sixteen years ago, the author began their PhD at UC Berkeley, where they were advised to focus on analytics rather than OLTP databases, which were considered a solved problem. However, upon developing Databricks, they found that OLTP databases were cumbersome, challenging to scale, and fragile. This led to the creation of Lakebase, a serverless Postgres database designed to address these issues by externalizing the write-ahead log (WAL) and data files into independent services. Lakebase architecture separates the WAL into a distributed service called SafeKeeper and data files into another service called PageServer, allowing for improved durability, scalability, and performance. This architecture eliminates data loss risks associated with disk failures and misconfigurations, simplifies high availability, and allows for elastic compute resources. Lakebase also introduces LTAP (Lake Transactional/Analytical Processing), which enables transactions and analytics to operate on a single data copy in real-time, avoiding the need for separate data copies and reducing costs. The system retains Postgres's ACID semantics while storing data in open columnar formats, making it accessible to both transactional and analytical engines without the delays and complexities of traditional replication methods. The architecture allows for unlimited storage, serverless compute, and instant branching, while ensuring that analytics can read the most current transactional data without affecting transactional workloads. LTAP aims to unify transactional and analytical processing by leveraging distinct compute engines for each workload while integrating at the storage layer.
Minecraft Dappled Forest Guide: How to Find, Structures, and More
AppWizard
June 30, 2026

Minecraft Dappled Forest Guide: How to Find, Structures, and More

The Dappled Forest biome in Minecraft is a new cold biome characterized by colorful Poplar trees, red shrubs, and shelf mushrooms, designed to evoke the essence of autumn with warm hues. It features Poplar trees in red, orange, or yellow, fallen Poplar trees, shelf mushrooms, red shrubs, leaf litter, brown mushrooms, and abandoned camps. Players can find this biome near colder areas like snowy tundras and taigas, and it includes various animal mobs such as sheep, cold chickens, cold cows, cold pigs, rabbits, and foxes.
MSYS2 And The No-Fuss Way To Get More GNU Into Your Windows
Winsage
June 22, 2026

MSYS2 And The No-Fuss Way To Get More GNU Into Your Windows

The Windows desktop experience has a streamlined interface, but its command line interface (CLI) offerings, particularly the cmd.exe shell, have been criticized for lacking the features found in UNIX/BSD/Linux environments. Microsoft’s transition to PowerShell has disappointed users who prefer a more traditional CLI experience. Despite Windows NT operating systems being POSIX compliant, they have historically lacked a suitable shell. MSYS2 provides a solution by offering a Linux-like experience with a Bash shell and the pacman package manager, allowing users to run shell scripts and access various tools. However, binaries compiled in MSYS2 may depend on shared libraries not included in the Windows system path. Upon installation, users can choose from different terminal options, with the UCRT terminal recommended for its usability. MSYS2 facilitates a streamlined development workflow, enabling the use of familiar tools across multiple platforms, but it does not achieve perfect integration within Windows and has some limitations, such as issues with stdout output in Bash.
Crysis 2 had problems, but it got one thing right: destruction
AppWizard
June 21, 2026

Crysis 2 had problems, but it got one thing right: destruction

Crysis 2 features a narrative centered around Alcatraz, a U.S. Marine caught in an alien invasion, guided by Prophet from the original Crysis. The game emphasizes destruction, transforming New York into a chaotic battleground, although it suffers from simplistic AI, a convoluted narrative, and clichéd characters. The nanosuit's functionality is reduced compared to its predecessor, limiting active abilities and creativity in gameplay. Players can use stealth and engage in direct combat, with standout moments during defensive missions where they assist civilians and demolish buildings to disrupt enemies. However, the final mission is anticlimactic, leaving players unsatisfied with the conclusion. Despite its limitations, Crysis 2 showcases moments of brilliance and potential for innovation in gaming.
Snowflake Postgres Unifies Your Apps, Analytics and AI
Tech Optimizer
June 18, 2026

Snowflake Postgres Unifies Your Apps, Analytics and AI

Every enterprise operates in two realms: one for real-time applications that process orders and engage customers, and another for analytics platforms that extract insights and drive AI. Snowflake is introducing Snowflake Postgres to bridge these realms with two key features: 1. Data mirroring, which is an always-on replication feature between Postgres and Snowflake, set to enter public preview soon. 2. Postgres for data lakes, allowing synchronization with analytics using open formats like Iceberg, which will be generally available shortly. These features aim to simplify the connection between transactional and analytical data, reducing the need for complex ETL pipelines. Customer feedback indicates that transferring data between OLTP and OLAP databases is the most challenging infrastructure task, leading to costs and issues such as data inconsistencies and delayed decision-making. Snowflake Postgres offers a simplified integration method with low-latency data mirroring that automatically maintains target tables in Snowflake to reflect the current state of source tables in Postgres. This setup can be configured easily through various interfaces or a single SQL command.
Snowflake Simplifies Postgres Data Sync
Tech Optimizer
June 17, 2026

Snowflake Simplifies Postgres Data Sync

Snowflake has introduced features to improve data integration between PostgreSQL and its platform, addressing challenges in transferring data between online transaction processing (OLTP) and online analytical processing (OLAP). One key feature is data mirroring, which offers low-latency replication for PostgreSQL, automatically maintaining target tables to reflect source changes with minimal setup effort. These advancements aim to simplify data integration, reduce costs associated with ETL tools, and facilitate real-time insights, enhancing operational efficiency for organizations.
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